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The scope of the journal includes research of the following types: the use of machine learning techniques to model real-world problems such as physical systems, social sciences, and biology; the development of novel numerical strategies, in conjunction of machine learning methods, to facilitate practical computation; and the fundamental mathematical and numerical analysis for understanding machine learning methods

Conservation Science and Practice publishes papers that address the policy, planning, and practice of conserving biological diversity.

High Frequency is an interdisciplinary journal on applied and theoretical topics devoted to high-frequency data questions, including high frequency data assimilation, analysis, methods for decision-making, mathematical and statistical modeling, empirical studies, computational theory and design, with applications to many topics including finance, astronomy, seismology, various other areas of physics and geosciences, environmental sciences, imaging applications such as in neuroscience.